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Abstract Background The natural light environment is far more complex than that experienced by animals under laboratory conditions. As a burrowing species, wild mice are able to self-modulate their light exposure, a concept known as light environment sampling behaviour. By contrast, under laboratory conditions mice have little opportunity to exhibit this behaviour. To address this issue, here we introduce a simple nestbox paradigm to allow mice to self-modulate their light environment. Dark nestboxes fitted with passive infrared sensors were used to monitor locomotor activity, circadian entrainment, decision making and light environment sampling behaviour. Results Under these conditions, mice significantly reduce their light exposure to an average of just 0.8 h across a 24 h period. In addition, mice show a distinct pattern of light environment sampling behaviour, with peaks at dawn and dusk under a ramped light dark cycle. Furthermore, we show that the timing of light environment sampling behaviour depends upon endogenous circadian rhythms and is abolished in mice lacking a circadian clock, indicating a feedback loop between light, the circadian clock and behaviour. Conclusions Our results highlight the important role of behaviour in modifying the light signals available for circadian entrainment under natural conditions.

Methane is a powerful greenhouse gas with a 25 times higher 100-year warming potential than carbon dioxide and is a target for mitigation to achieve climate goals. To control and curb methane emissions, estimates are required from the sources and sectors which are typically generated using bottom-up methods. However, recent studies have shown that national and international bottom-up approaches can significantly underestimate emissions. In this study, we present three bottom-up approaches used to estimate methane emissions from all emission sectors in the Denver-Julesburg basin, CO, USA. Our data show emissions generated from all three methods are lower than historic measurements. A Tier 1/2 approach using IPCC emission factors estimated 2022 methane emissions of 358 Gg (0.8% of produced methane lost by the energy sector), while a Tier 3 EPA-based approach estimated emissions of 269 Gg (0.2%). Using emission factors informed by contemporary and region-specific measurement studies, emissions of 212 Gg (0.2%) were calculated. The largest difference in emissions estimates were a result of using the Mechanistic Air Emissions Simulator (MAES) for the production and transport of oil and gas in the DJ basin. The MAES accounts for changes to regulatory practice in the DJ basin, which include comprehensive requirements for compressors, pneumatics, equipment leaks, and fugitive emissions, which were implemented to reduce emissions starting in 2014. The measurement revealed that normalized gas loss is predicted to have been reduced by a factor of 20 when compared to 10-year-old normalization loss measurements and a factor of 10 less than a nearby oil and production area (Delaware basin, TX); however, we suggest that more measurements should be made to ensure that the long-tail emission distribution has been captured by the modeling. This study suggests that regulations implemented by the Colorado Department of Public Health and Environment could have reduced emissions by a factor of 20, but contemporary regional measurements should be made to ensure these bottom-up calculations are realistic.

Abstract Background We have previously discovered clusters of sequentially negative and positive modulators of acute inflammation during cytokine stimulation in epithelial cells and identified potential targets for therapy within these clusters. MAP3K8 is a druggable kinase that we found to be a hub of a principal interaction network. We describe here the results of MAP3K8 knockdown in the A549 lung cancer cell line, the BEAS-2B epithelial cell line and normal human bronchial epithelial (NHBE) cells following IL-1β stimulation. We analysed signalling transduction and global gene expression after IL-1β stimulation with and without MAP3K8 knockdown, quantifying levels of the inflammatory cytokines IL-6, IL-8 and RANTES levels by qPCRs and/or by ELISAs. We also examined potential small molecule inhibitors for MAP3K8 in the same models. Results IL-1β significantly and consistently increased MAP3K8 expression after 2 h in A549, BEAS-2B and NHBE cells. Phosphorylation of MAP3K8 occurred at 20 min after IL-1β stimulation and MAP3K8 protein was degraded at 30 min. MAP3K8 knockdown significantly reduced IL-6, IL-8 levels after IL-1β stimulation and yielded a 10-fold enhancement of the anti-inflammatory effects of dexamethasone. Phosphorylation of ERK1/2 (P-ERK1/2) and phosphorylation of SAPK/JNK (P-SAPK/JNK) decreased at 30 min after IL-1β stimulation with MAP3K8 knockdown. The combination of dexamethasone and MAP3K8 knockdown resulted in greater inhibition of phosphorylated ERK1/2 and SAPK/JNK. Nineteen genes including MMP1, MMP3, MMP10, ITGB8, LAMC2 and PLAT (P corrected

Abstract. Introduction:. Chronic pain is a hallmark of joint diseases. Although these conditions are often accompanied by negative affective symptoms including depression and anxiety, these comorbidities are rarely studied simultaneously in preclinical models where they are poorly characterised. Moreover, how affective symptoms relate to the more obvious sensory and functional symptoms of joint diseases is not well understood. Here, we have addressed these gaps in knowledge. Methods:. We used 2 preclinical models of joint pain in male mice and an array of behavioural and molecular assays to fully characterise functional deficits, mechanical hypersensitivity, affective symptoms, and nociceptive signaling in joint pain, as well as investigate their relationship. Results:. Ankle joint inflammation and knee osteoarthritis induced mechanical hypersensitivity that lasted at least 3 months and that was not different between the 2 models on most days. However, the models presented with markedly different weight-bearing deficits, molecular profiles, and affective outcomes. Specifically, only the model of knee osteoarthritis was accompanied by an increase in negative affective behaviors, including early changes in circadian patterns, persistent cognitive impairments, and late development of depressive-like behavior. Importantly, the early weight-bearing deficit strongly correlated with the emotional profiles and the hypersensitivity at 3 months, suggesting that early objective functional measures may be used as predictors of long-term affective symptoms and pain. Conclusion:. The predictive value of early weight-bearing deficit could prove useful in the clinical setting for adapted therapeutic approaches for the prevention of emotional comorbidities and better pain management for patients with joint pain.

Glaciers in Afghanistan are crucial elements for water resource and summer river flows. They are also threatened by rapid climate warming. This study presents an up-to-date assessment of ice cover loss for the entire country over two periods, 2000–2008 and 2008–2020, using newly developed remote sensing indices that include a more reliable determination of changing debris cover. The results suggest an estimated ice-covered area of 2,690.7 ± 108.2 km2 in 2020, that was 75 ± 0.7% clean ice and 25 ± 3.0 percent debris-covered ice. Total ice-covered area retreated by −0.16 ± 0.01 percent yr−1 between 2000 and 2008 and −0.46 ± 0.05 percent yr−1 between 2008 and 2020. Notably, 60 percent of ice cover loss (2000–2020) related to ice cover extents with a size ≤ 2.5 km2, comprising 60 percent of the total ice-covered area in 2000. Higher altitude accumulation zones also exhibited mass loss. However, there was also substantial spatial variation in these rates of loss based on geographical region, glacier size, and climate zones. In the north-eastern regions that are geographically close to or part of the north-west Karakoram ice cover was declining at a substantially lower rate, stable, or even increasing slightly, as compared with the northern and central regions of Afghanistan.

Abstract Background Serrated polyposis syndrome is the most common polyposis syndrome that has neoplastic potential. However, the natural history, genetic basis, and risk of dysplasia and neoplasia of serrated polyposis syndrome are incompletely understood. The objective of this study is to define the epidemiology of serrated polyposis syndrome. Using this data, we aim to evaluate candidate variables for predicting the risk of dysplasia and neoplasia in sessile serrated lesions found in serrated polyposis syndrome patients. Finally, we aim to use this data to create and evaluate clinical prediction models for accuracy in predicting dysplastic sessile serrated lesions in serrated polyposis syndrome patients. Methods This was a regional Australian single-centre retrospective cohort study. Data was prospectively collected data from the clinical record database of a regional Australian gastroenterology practice. All patients undergoing colonoscopy at Port Macquarie Gastroenterology between January 2015 and September 2021 were screened for this study. Collected data included patient demographic, endoscopic, and histopathological findings. Clinical and endoscopic multivariate logistic regression models were created to predict dysplastic sessile serrated lesions. Model performance was examined using the area under the receiver operating curve. Results In total 8401 patients underwent a colonoscopy procedure during the study period. Serrated polyposis syndrome was diagnosed in 247, representing a prevalence of 2.94% (mean age 67.15 years, 62.75% female). Logistic regression identified; older age at serrated polyposis syndrome diagnosis, a personal history of colorectal cancer, size of the largest sessile serrated lesions removed, and total sessile serrated lesions count as predictors of dysplastic sessile serrated lesions. The clinical and endoscopic model had an area under the receiver operating curve of 0.75. Conclusion Serrated polyposis syndrome is more common than previously described. The clinical and endoscopic variables identified in logistic regression have acceptable accuracy in predicting the risk of dysplasia, however other populations need to be studied to achieve generalisability and improve model performance.

Abstract One of the major consequences of the COVID-19 pandemic has been the significant incidence of persistent fatigue following resolution of an acute infection (i.e. post-COVID fatigue). We have shown previously that, in comparison to healthy controls, those suffering from post-COVID fatigue exhibit changes in muscle physiology, cortical circuitry, and autonomic function. Whether these changes preceded infection, potentially predisposing people to developing post-COVID fatigue, or whether the changes were a consequence of infection was unclear. Here we present results of a 12-month longitudinal study of 18 participants from the same cohort of post-COVID fatigue sufferers to investigate these correlates of fatigue over time. We report improvements in self-perception of the impact of fatigue via questionnaires, as well as significant improvements in objective measures of peripheral muscle fatigue and autonomic function, bringing them closer to healthy controls. Additionally, we found reductions in muscle twitch tension rise times, becoming faster than controls, suggesting that the improvement in muscle fatigability might be due to a process of adaptation rather than simply a return to baseline function.

Quantifying methane emissions is essential for meeting near-term climate goals and is typically carried out using methane concentrations measured downwind of the source. One major source of methane that is important to observe and promptly remediate is fugitive emissions from oil and gas production sites but installing methane sensors at the thousands of sites within a production basin is expensive. In recent years, relatively inexpensive metal oxide sensors have been used to measure methane concentrations at production sites. Current methods used to calibrate metal oxide sensors have been shown to have significant shortcomings, resulting in limited confidence in methane concentrations generated by these sensors. To address this, we investigate using machine learning (ML) to generate a model that converts metal oxide sensor output to methane mixing ratios. To generate test data, two metal oxide sensors, TGS2600 and TGS2611, were collocated with a trace methane analyzer downwind of controlled methane releases. Over the duration of the measurements, the trace gas analyzer’s average methane mixing ratio was 2.40 ppm with a maximum of 147.6 ppm. The average calculated methane mixing ratios for the TGS2600 and TGS2611 using the ML algorithm were 2.42 ppm and 2.40 ppm, with maximum values of 117.5 ppm and 106.3 ppm, respectively. A comparison of histograms generated using the analyzer and metal oxide sensors mixing ratios shows overlap coefficients of 0.95 and 0.94 for the TGS2600 and TGS2611, respectively. Overall, our results showed there was a good agreement between the ML-derived metal oxide sensors’ mixing ratios and those generated using the more accurate trace gas analyzer. This suggests that the response of lower-cost sensors calibrated using ML could be used to generate mixing ratios with precision and accuracy comparable to higher priced trace methane analyzers. This would improve confidence in low-cost sensors’ response, reduce the cost of sensor deployment, and allow for timely and accurate tracking of methane emissions.

Debris-covered ice is widespread in mountain regions with debris an important control on surface ice melt and glacier retreat. Quantifying debris cover extent and its evolution through time over large regions remains a challenge. This study develops two Normalized Difference Supraglacial Debris Indices for mapping debris-covered ice based on thermal and near Infrared Landsat 8 bands. They were calibrated with field data. Validation suggests that they have a high level of accuracy. They are then applied to Landsat data for 2016 to produce the first detailed glacier inventory of the Afghanistan Hindu Kush Himalaya that includes debris cover. 3408 glaciers were identified which, for those ⩾0.01 km2 in area, gives an ice cover of 2,222 ± 11 km2 and a debris cover of 619 ± 40 km2. Principal components analysis was used to identify the most influential drivers of debris-covered ice extent. Lower proportions of debris cover were associated with glaciers with a higher elevation range, that were larger, longer and wider. These relations were statistically clearer when the dataset was broken down into climate and geological zones. A glaciers continue to shrink, the proportion of debris cover will become higher, making it more important to map debris cover reliably.

Light enables vision and exerts widespread effects on physiology and behavior, including regulating circadian rhythms, sleep, hormone synthesis, affective state, and cognitive processes. Appropriate lighting in animal facilities may support welfare and ensure that animals enter experiments in an appropriate physiological and behavioral state. Furthermore, proper consideration of light during experimentation is important both when it is explicitly employed as an independent variable and as a general feature of the environment. This Consensus View discusses metrics to use for the quantification of light appropriate for nonhuman mammals and their application to improve animal welfare and the quality of animal research. It provides methods for measuring these metrics, practical guidance for their implementation in husbandry and experimentation, and quantitative guidance on appropriate light exposure for laboratory mammals. The guidance provided has the potential to improve data quality and contribute to reduction and refinement, helping to ensure more ethical animal use.

Non-invasive vagus nerve stimulation (nVNS) is an established neurostimulation therapy used in the treatment of epilepsy, migraine and cluster headache. In this randomized, double-blind, sham-controlled trial we explored the role of nVNS in the treatment of gait and other motor symptoms in Parkinson’s disease (PD) patients. In a subgroup of patients, we measured selected neurotrophins, inflammatory markers and markers of oxidative stress in serum. Thirty-three PD patients with freezing of gait (FOG) were randomized to either active nVNS or sham nVNS. After baseline assessments, patients were instructed to deliver six 2 min stimulations (12 min/day) of the active nVNS/sham nVNS device for 1 month at home. Patients were then re-assessed. After a one-month washout period, they were allocated to the alternate treatment arm and the same process was followed. Significant improvements in key gait parameters (speed, stance time and step length) were observed with active nVNS. While serum tumor necrosis factor- α decreased, glutathione and brain-derived neurotrophic factor levels increased significantly (p

Quantifying and controlling fugitive methane emissions from oil and gas facilities remains essential for addressing climate goals, but the costs associated with monitoring millions of production sites remain prohibitively expensive. Current thinking, supported by measurement and simple dispersion modelling, assumes single-digit parts-per-million instrumentation is required. To investigate instrument response, the inlets of three trace-methane (sub-ppm) analyzers were collocated on a facility designed to release gas of known composition at known flow rates between 0.4 and 5.2 kg CH4 h−1 from simulated oil and gas infrastructure. Methane mixing ratios were measured by each instrument at 1 Hertz resolution over nine hours. While mixing ratios reported by a cavity ring-down spectrometer (CRDS)-based instrument were on average 10.0 ppm (range 1.8 to 83 ppm), a mid-infrared laser absorption spectroscopy (MIRA)-based instrument reported short-lived mixing ratios far larger than expected (range 1.8 to 779 ppm) with a similar nine-hour average to the CRDS (10.1 ppm). We suggest the peaks detected by the MIRA are likely caused by a micrometeorological phenomenon, where vortex shedding has resulted in heterogeneous methane plumes which only the MIRA can observe. Further analysis suggests an instrument like the MIRA (an optical-cavity-based instrument with cavity size ≤10 cm3 measuring at ≥2 Hz with air flow rates in the order of ≤0.3 slpm at distances of ≤20 m from the source) but with a higher detection limit (25 ppm) could detect enough of the high-concentration events to generate representative 20 min-average methane mixing ratios. Even though development of a lower-cost, high-precision, high-accuracy instrument with a 25 ppm detection threshold remains a significant problem, this has implications for the use of instrumentation with higher detection thresholds, resulting in the reduction in cost to measure methane emissions and providing a mechanism for the widespread deployment of effective leak detection and repair programs for all oil and gas infrastructure.

Climate change accelerates glacier retreat, leading to extensive exposure of sediment to light and ecological succession. Succession has traditionally been studied as a chronosequence, where vegetation development is directly correlated with time since glacier retreat or distance from the retreating glacier margin. More recent work has challenged this model, arguing that succession seems to be mainly influenced by heterogeneous conditions at the local scale. The aim of this study was to identify the factors influencing the local-scale establishment of plant communities following glacier recession. Vascular plants and their cover were inventoried in 100 plots (1 m2) for a thirty-year-old alluvial plain in front of the Otemma glacier (Swiss Alps). Depth to water table, distance to the glacial main river and to the nearest channel, sediment size, moss, lichen, and biological soil crust cover were measured. Results showed that proglacial margins develop hydrological heterogeneity over a small scale, reflected in the four observed plant communities. These range from the dry Sempervivum-dominated community, on gravel-rich sediments with a deep water table, to the Trifolium-dominated community, close to secondary channels, with the highest plant cover and species richness and incorporating grassland species. Heterogeneity in water availability exerted a critical control on vegetation development.

Methane is a greenhouse gas and identified as a key driver of near-term climate change. Bottom-up approaches estimate annual methane loss from US natural gas production and transport at 6 Tg, but recent studies suggest this may be an underestimate. To investigate this possibility, an equipment-based emissions inventory, using EPA emission factors, was developed to calculate methane emissions from oil and gas operations in the Delaware basin, USA. Emission factors and activity data were then updated using contemporary and region-specific measurement data. The original inventory estimated emissions at 315 Gg CH4 y−1 (gas production-normalized rate of 0.6% loss), while the updated inventory estimated emissions of 1500 Gg CH4 y−1 (2.8% loss). The largest changes resulted from large fugitive emissions from oil production (+430 Gg CH4 y−1), updating maintenance activity emissions (+214 Gg CH4 y−1), considering flaring inefficiency (+174 Gg CH4 y−1), and the inclusion of associated gas venting (+136 Gg CH4 y−1). This study suggests that a systematic underestimate probably exists in current bottom-up inventories and identifies sources currently missing or may be incorrect. We also strongly recommend that emission factors should be validated through direct comparison against measurement campaigns that include long-tail distributions typical of oil and gas activities.

The EDGE-CALIFA survey provides spatially resolved optical integral-field unit and CO spectroscopy for 125 galaxies selected from the Calar Alto Legacy Integral Field Area Survey (CALIFA) Data Release 3 sample. The Extragalactic Database for Galaxy Evolution (EDGE) presents the spatially resolved products of the survey as pixel tables that reduce the oversampling in the original images and facilitate comparison of pixels from different images. By joining these pixel tables to lower-dimensional tables that provide radial profiles, integrated spectra, or global properties, it is possible to investigate the dependence of local conditions on large-scale properties. The database is freely accessible and has been utilized in several publications. We illustrate the use of this database and highlight the effects of CO upper limits on the inferred slopes of the local scaling relations between the stellar mass, star formation rate (SFR), and H _2 surface densities. We find that the correlation between H _2 and SFR surface density is the tightest among the three relations.

We present a ^12 CO( J = 2−1) survey of 60 local galaxies using data from the Atacama Compact Array as part of the Extragalactic Database for Galaxy Evolution: the ACA EDGE survey. These galaxies all have integral field spectroscopy from the CALIFA survey. Compared to other local galaxy surveys, ACA EDGE is designed to mitigate selection effects based on CO brightness and morphological type. Of the 60 galaxies in ACA EDGE, 36 are on the star formation main sequence, 13 are on the red sequence, and 11 lie in the “green valley” transition between these sequences. We test how star formation quenching processes affect the star formation rate (SFR) per unit molecular gas mass, SFE _mol = SFR/ M _mol , and related quantities in galaxies with stellar masses 10 ≤ log[ M _⋆ / M _⊙ ] ≤ 11.5 covering the full range of morphological types. We observe a systematic decrease of the molecular-to-stellar mass fraction ( ${R}_{\star }^{\mathrm{mol}}$ ) with a decreasing level of star formation activity, with green valley galaxies also having lower SFE _mol than galaxies on the main sequence. On average, we find that the spatially resolved SFE _mol within the bulge region of green valley galaxies is lower than in the bulges of main-sequence galaxies if we adopt a constant CO-to-H _2 conversion factor, α _CO . While efficiencies in main-sequence galaxies remain almost constant with galactocentric radius, in green valley galaxies, we note a systematic increase of SFE _mol , ${R}_{\star }^{\mathrm{mol}}$ , and specific SFR with increasing radius. As shown in previous studies, our results suggest that although gas depletion (or removal) seems to be the most important driver of the star formation quenching in galaxies transiting through the green valley, a reduction in star formation efficiency is also required during this stage.

During inherited retinal degenerations (IRDs), vision is lost due to photoreceptor cell death; however, a range of optogenetic tools have been shown to restore light responses in animal models. Restored response characteristics vary between tools and the neuronal cell population to which they are delivered: the interplay between these is complex, but targeting upstream neurons (such as retinal bipolar cells) may provide functional benefit by retaining intraretinal signal processing. In this study, our aim was to compare two optogenetic tools: mammalian melanopsin (hOPN4) and microbial red-shifted channelrhodopsin (ReaChR) expressed within two subpopulations of surviving cells in a degenerate retina. Intravitreal adeno-associated viral vectors and mouse models utilising the Cre/lox system restricted expression to populations dominated by bipolar cells or retinal ganglion cells and was compared with non-targeted delivery using the chicken beta actin (CBA) promoter. In summary, we found bipolar-targeted optogenetic tools produced faster kinetics and flatter intensity-response relationships compared with non-targeted or retinal-ganglion-cell-targeted hOPN4. Hence, optogenetic tools of both mammalian and microbial origins show advantages when targeted to bipolar cells. This demonstrates the advantage of bipolar-cell-targeted optogenetics for vision restoration in IRDs. We therefore developed a bipolar-cell-specific gene delivery system employing a compressed promoter with the potential for clinical translation.

The recent interest in measuring methane (CH4) emissions from abandoned oil and gas wells has resulted in five methods being typically used. In line with the US Federal Orphaned Wells Program’s (FOWP) guidelines and the American Carbon Registry’s (ACR) protocols, quantification methods must be able to measure minimum emissions of 1 g of CH4 h−1 to within ±20%. To investigate if the methods meet the required standard, dynamic chambers, a Hi-Flow (HF) sampler, and a Gaussian plume (GP)-based approach were all used to quantify a controlled emission (Qav; g h−1) of 1 g of CH4 h−1. After triplicate experiments, the average accuracy (Ar; %) and the upper (Uu; %) and lower (Ul; %) uncertainty bounds of all methods were calculated. Two dynamic chambers were used, one following the ACR guidelines, and a second “mobile” chamber made from lightweight materials that could be constructed around a source of emission on a well head. The average emission calculated from the measurements made using the dynamic chamber (Qav = 1.01 g CH4 h−1, Ar = +0.9%), the mobile chamber (Qav = 0.99 g CH4 h−1, Ar = −1.4%), the GP approach (Qav = 0.97 g CH4 h−1, Ar = −2.6%), and the HF sampler (Qav = 1.02 g CH4 h−1, Ar = +2.2%) were all within ±3% of 1 g of CH4 h−1 and met the requirements of the FOWP and ACR protocols. The results also suggest that the individual measurements made using the dynamic chamber can quantify emissions of 1 g of CH4 h−1 to within ±6% irrespective of the design (material, number of parts, geometrical shape, and hose length), and changes to the construction or material specifications as defined via ACR make no discernible difference to the quantification uncertainty. Our tests show that a collapsible chamber can be easily constructed around the emission source on an abandoned well and be used to quantify emissions from abandoned wells in remote areas. To our knowledge, this is the first time that methods for measuring the CH4 emissions of 1 g of CH4 h−1 have been quantitively assessed against a known reference source and against each other.

Natural gas (NG) leaks from below-ground pipelines pose safety, economic, and environmental hazards. Despite walking surveys using handheld methane (CH4) detectors to locate leaks, accurately triaging the severity of a leak remains challenging. It is currently unclear whether CH4 detectors used in walking surveys could be used to identify large leaks that require an immediate response. To explore this, we used above-ground downwind CH4 concentration measurements made during controlled emission experiments over a range of environmental conditions. These data were then used as the input to a novel modeling framework, the ESCAPE−1 model, to estimate the below-ground leak rates. Using 10-minute averaged CH4 mixing/meteorological data and filtering out wind speed < 2 m s−1/unstable atmospheric data, the ESCAPE−1 model estimates small leaks (0.2 kg CH4 h−1) and medium leaks (0.8 kg CH4 h−1) with a bias of −85%/+100% and −50%/+64%, respectively. Longer averaging (≥3 h) results in a 55% overestimation for small leaks and a 6% underestimation for medium leaks. These results suggest that as the wind speed increases or the atmosphere becomes more stable, the accuracy and precision of the leak rate calculated by the ESCAPE−1 model decrease. With an uncertainty of ±55%, our results show that CH4 mixing ratios measured using industry-standard detectors could be used to prioritize leak repairs.

We explore the relationship between mid-infrared (mid-IR) and CO rotational line emission from massive star-forming galaxies, which is one of the tightest scalings in the local universe. We assemble a large set of unresolved and moderately (∼1 kpc) spatially resolved measurements of CO (1–0) and CO (2–1) intensity, I _CO , and mid-IR intensity, I _MIR , at 8, 12, 22, and 24 μ m. The I _CO versus I _MIR relationship is reasonably described by a power law with slopes 0.7–1.2 and normalization I _CO ∼ 1 K km s ^−1 at I _MIR ∼ 1 MJy sr ^−1 . Both the slopes and intercepts vary systematically with choice of line and band. The comparison between the relations measured for CO (1–0) and CO (2–1) allow us to infer that ${R}_{21}\propto {I}_{\mathrm{MIR}}^{0.2}$ , in good agreement with other work. The 8 μ m and 12 μ m bands, with strong polycyclic aromatic hydrocarbon (PAH) features, show steeper CO versus mid-IR slopes than the 22 and 24 μ m, consistent with PAH emission arising not just from CO-bright gas but also from atomic or CO-dark gas. The CO-to-mid-IR ratio correlates with global galaxy stellar mass ( M _⋆ ) and anticorrelates with star formation rate/ M _⋆ . At ∼1 kpc resolution, the first four PHANGS–JWST targets show CO-to-mid-IR relationships that are quantitatively similar to our larger literature sample, including showing the steep CO-to-mid-IR slopes for the JWST PAH-tracing bands, although we caution that these initial data have a small sample size and span a limited range of intensities.

Glacier shrinkage opens new proglacial terrain with pronounced environmental gradients along longitudinal and lateral chronosequences. Despite the environmental harshness of the streams that drain glacier forelands, their benthic biofilms can harbor astonishing biodiversity spanning all domains of life. Here, we studied the spatial dynamics of prokaryotic and eukaryotic photoautotroph diversity within braided glacier-fed streams and tributaries draining lateral terraces predominantly fed by groundwater and snowmelt across three proglacial floodplains in the Swiss Alps. Along the lateral chronosequence, we found that benthic biofilms in tributaries develop higher biomass than those in glacier-fed streams, and that their respective diversity and community composition differed markedly. We also found spatial turnover of bacterial communities in the glacier-fed streams along the longitudinal chronosequence. These patterns along the two chronosequences seem unexpected given the close spatial proximity and connectivity of the various streams, suggesting environmental filtering as an underlying mechanism. Furthermore, our results suggest that photoautotrophic communities shape bacterial communities across the various streams, which is understandable given that algae are the major source of organic matter in proglacial streams. Overall, our findings shed new light on benthic biofilms in proglacial streams now changing at rapid pace owing to climate-induced glacier shrinkage.

The impact of “moral injury” (MI) among deployed veterans, defined as actions in combat that violate a veteran's moral beliefs and result in psychological distress, has increasingly become a significant clinical concern separate from other trauma- and stressor-related disorders. MI involves severe distress over violations of core beliefs often followed by feelings of guilt and conflict and is common among veterans with PTSD. While the psychological impact of PTSD is well-documented among veterans, this has been done less so with respect to MI. We studied MI among 1,032 deployed veterans who were outpatients in a large non-profit multi-hospital system in central Pennsylvania. The study included active duty and Guard/Reserve members, as well as veterans who were not Department of Veterans Affairs (VA) service users. Our hypothesis was that, controlling for other risk factors, veterans with high MI would have current mental disorders. Our secondary hypothesis was that MI would be associated with other psychopathologies, including chronic pain, sleep disorders, fear of death, anomie, and use of alcohol/drugs to cope post deployment. Most veterans studied were deployed to Vietnam (64.1%), while others were deployed to post-Vietnam conflicts in Iraq and Afghanistan and elsewhere. Altogether, 95.1% of the veterans were male and their mean age was 61.6 years (SD = 11.8). Among the veterans, 24.4% had high combat exposure, 10.9% had PTSD, 19.8% had major depressive disorder, and 11.7% had a history of suicidal thoughts. Based on the Moral Injury Events Scale (MIES), 25.8% had high MI post deployment, defined as a score above the 75th percentile. Results show that high MI among veterans was associated with current global mental health severity and recent mental health service use, but not suicidal thoughts. In addition, as hypothesized, MI was also associated with pain, sleep disorders, fear of death, anomie, use of alcohol/drugs to cope post-deployment, and poor unit support/morale during deployment. Deployed veterans with MI are more likely to have current mental health disorders and other psychological problems years after deployment. Further research is advised related to the screening, assessment, treatment, and prevention of MI among veterans and others after trauma exposures.

Mistimed exposure to light has been demonstrated to negatively affect multiple aspects of physiology and behavior. Here we analyzed the effects of chronic exposure to abnormal lighting conditions in mice. We exposed mice for 1 year to either: a standard light/dark cycle, a “light-pollution” condition in which low levels of light were present in the dark phase of the circadian cycle (dim light at night, DLAN), or altered light cycles in which the length of the weekday and weekend light phase differed by 6 h (“social jetlag”). Mice exhibited several circadian activity phenotypes, as well as changes in motor function, associated particularly with the DLAN condition. Our data suggest that these phenotypes might be due to changes outside the core clock. Dendritic spine changes in other brain regions raise the possibility that these phenotypes are mediated by changes in neuronal coordination outside of the clock. Given the prevalence of artificial light exposure in the modern world, further work is required to establish whether these negative effects are observed in humans as well.

Ocular light exposure has important influences on human health and well-being through modulation of circadian rhythms and sleep, as well as neuroendocrine and cognitive functions. Prevailing patterns of light exposure do not optimally engage these actions for many individuals, but advances in our understanding of the underpinning mechanisms and emerging lighting technologies now present opportunities to adjust lighting to promote optimal physical and mental health and performance. A newly developed, international standard provides a SI-compliant way of quantifying the influence of light on the intrinsically photosensitive, melanopsin-expressing, retinal neurons that mediate these effects. The present report provides recommendations for lighting, based on an expert scientific consensus and expressed in an easily measured quantity (melanopic equivalent daylight illuminance (melaponic EDI)) defined within this standard. The recommendations are supported by detailed analysis of the sensitivity of human circadian, neuroendocrine, and alerting responses to ocular light and provide a straightforward framework to inform lighting design and practice. Light exposure influences human health and wellbeing by modulating circadian rhythms and sleep. This Consensus View outlines the first expert scientific consensus recommendations for appropriate daily patterns of light exposure to promote health and wellbeing and inform lighting design and practice.

Studying higher brain function presents fundamental scientific challenges but has great potential for impactful translation to the clinic, supporting the needs of many patients suffering from conditions that relate to neuronal dysfunction. For many key questions relevant to human neurological conditions and clinical interventions, non-human primates (NHPs) remain the only suitable model organism and the only effective way to study the relationship between brain structure and function with the knowledge and tools currently available. Here we present three exemplary studies of current research yielding important findings that are directly translational to human clinical patients but which would be impossible without NHP studies. Our first example shows how studies of the NHP prefrontal cortex are leading to clinically relevant advances and potential new treatments for human neuropsychiatric disorders such as depression and anxiety. Our second example looks at the relevance of NHP research to our understanding of visual pathways and the visual cortex, leading to visual prostheses that offer treatments for otherwise blind patients. Finally, we consider recent advances in treatments leading to improved recovery of movement and motor control in stroke patients, resulting from our improved understanding of brain stem parallel pathways involved in movement in NHPs. The case for using NHPs in neuroscience research, and the direct benefits to human patients, is strong but has rarely been set out directly. This paper reviews three very different areas of neuroscience research, expressly highlighting the unique insights offered to each by NHP studies and their direct applicability to human clinical conditions.

Light is known to exert powerful effects on behavior and physiology, including upon the amount and distribution of activity across the day/night cycle. Here we use home cage activity monitoring to measure the effect of differences in home cage light spectrum and intensity on key circadian activity parameters in mice. Due to the relative positioning of any individually ventilated cage (IVC) with regard to the animal facility lighting, notable differences in light intensity occur across the IVC rack. Although all mice were found to be entrained, significant differences in the timing of activity onset and differences in activity levels were found between mice housed in standard versus red filtering cages. Furthermore, by calculating the effective irradiance based upon the known mouse photopigments, a significant relationship between light intensity and key circadian parameters are shown. Perhaps unsurprisingly given the important role of the circadian photopigment melanopsin in circadian entrainment, melanopic illuminance is shown to correlate more strongly with key circadian activity parameters than photopic lux. Collectively, our results suggest that differences in light intensity may reflect an uncharacterized source of variation in laboratory rodent research, with potential consequences for reproducibility. Room design and layout vary within and between facilities, and caging design and lighting location relative to cage position can be highly variable. We suggest that cage position should be factored into experimental design, and wherever possible, experimental lighting conditions should be characterized as a way of accounting for this source of variation.

We present ^13 CO( J = 1 → 0) observations for the EDGE-CALIFA survey, which is a mapping survey of 126 nearby galaxies at a typical spatial resolution of 1.5 kpc. Using detected ^12 CO emission as a prior, we detect ^13 CO in 41 galaxies via integrated line flux over the entire galaxy and in 30 galaxies via integrated line intensity in resolved synthesized beams. Incorporating our CO observations and optical IFU spectroscopy, we perform a systematic comparison between the line ratio ${{ \mathcal R }}_{12/13}\equiv I{[}^{12}\mathrm{CO}(J=1\to 0)]/I{[}^{13}\mathrm{CO}(J=1\to 0)]$ and the properties of the stars and ionized gas. Higher ${{ \mathcal R }}_{12/13}$ values are found in interacting galaxies compared to those in noninteracting galaxies. The global ${{ \mathcal R }}_{12/13}$ slightly increases with infrared color F _60 / F _100 but appears insensitive to other host-galaxy properties such as morphology, stellar mass, or galaxy size. We also present azimuthally averaged ${{ \mathcal R }}_{12/13}$ profiles for our sample up to a galactocentric radius of 0.4 r _25 (∼6 kpc), taking into account the ^13 CO nondetections by spectral stacking. The radial profiles of ${{ \mathcal R }}_{12/13}$ are quite flat across our sample. Within galactocentric distances of 0.2 r _25 , the azimuthally averaged ${{ \mathcal R }}_{12/13}$ increases with the star formation rate. However, Spearman rank correlation tests show the azimuthally averaged ${{ \mathcal R }}_{12/13}$ does not strongly correlate with any other gas or stellar properties in general, especially beyond 0.2 r _25 from the galaxy centers. Our findings suggest that in the complex environments in galaxy disks, ${{ \mathcal R }}_{12/13}$ is not a sensitive tracer for ISM properties. Dynamical disturbances, like galaxy interactions or the presence of a bar, also have an overall impact on ${{ \mathcal R }}_{12/13}$ , which further complicates the interpretations of ${{ \mathcal R }}_{12/13}$ variations.

Abstract The Bengal Basin preserves the erosional signals of coupled tectonic‐climatic change during late Cenozoic development of the Himalayan orogen, yet regional correlation and interpretation of these signals remains incomplete. We present a new geologic map of fluvial‐deltaic deposits of the Indo‐Burman Ranges (IBR), five detrital zircon fission track analyses, and twelve high‐n detrital zircon U‐Pb age distributions (dzUPb) from the Barail (late Eocene–early Miocene), Surma (early–late Miocene), and Tipam (late Miocene–Pliocene) Groups of the ancestral Brahmaputra delta. We use dzUPb statistical tests to correlate the IBR units with equivalent age strata throughout the Bengal Basin. An influx of trans‐Himalayan sediment and the first appearance of ∼50 Ma grains of the Gangdese batholith in the lower Surma Group (∼18–15 Ma) records the early Miocene arrival of the ancestral Brahmaputra delta to the Bengal Basin. Contributions from Himalayan sources systematically decrease up section through the late Miocene as the contribution of Trans‐Himalayan Arc sources increases. The Miocene (∼18–8 Ma) deposition of the Surma Group records upstream expansion of the ancestral Brahmaputra River into southeastern Tibet. Late Miocene (

Methane (CH4), a powerful greenhouse gas (GHG), has been identified as a key target for emission reduction in the Paris agreement, but it is not currently clear where efforts should be focused to make the greatest impact. Currently, activity data and standard emission factors (EF) are used to generate GHG emission inventories. Many of the EFs are globally uniform and do not account for regional variability in industrial or agricultural practices and/or regulation. Regional EFs can be derived from top–down emissions measurements and used to make bespoke regional GHG emission inventories that account for geopolitical and social variability. However, most large-scale top–down approaches campaigns require significant investment. To address this, lower-cost driving surveys (DS) have been identified as a viable alternative to more established methods. DSs can take top–down measurements of many emission sources in a relatively short period of time, albeit with a higher uncertainty. To investigate the use of a portable measurement system, a 2260 km DS was conducted throughout the Denver–Julesburg Basin (DJB). The DJB covers an area of 8000 km2 north of Denver, CO and is densely populated with CH4 emission sources, including oil and gas (O and G) operations, agricultural operations (AGOs), lakes and reservoirs. During the DS, 157 individual CH4 emission sources were detected; 51%, 43% and 4% of sources were AGOs, O and G operations, and natural sources, respectively. Methane emissions from each source were quantified using downwind concentration and meteorological data and AGOs and O and G operations represented nearly all the CH4 emissions in the DJB, accounting for 54% and 37% of the total emission, respectively. Operations with similar emission sources were grouped together and average facility emission estimates were generated. For agricultural sources, emissions from feedlot cattle, dairy cows and sheep were estimated at 5, 31 and 1 g CH4 head−1 h−1, all of which agreed with published values taken from focused measurement campaigns. Similarly, for O and G average emissions for well pads, compressor stations and gas processing plants (0.5, 14 and 110 kg CH4 facility−1 h−1) were in reasonable agreement with emission estimates from intensive measurement campaigns. A comparison of our basin wide O and G emissions to measurements taken a decade ago show a decrease of a factor of three, which can feasibly be explained by changes to O and G regulation over the past 10 years, while emissions from AGOs have remained constant over the same time period. Our data suggest that DSs could be a low-cost alternative to traditional measurement campaigns and used to screen many emission sources within a region to derive representative regionally specific and time-sensitive EFs. The key benefit of the DS is that many regions can be screened and emission reduction targets identified where regional EFs are noticeably larger than the regional, national or global averages.

The crystalline basement and Caledonian orogenic belt of East Greenland between 70 and 78° N are divided into five source regions on the basis of heavy mineral assemblages, mineral geochemistry, and isotopic age data from 42 modern moraine/outwash samples. The sand types generated by the five source regions can be recognized in the Mesozoic sedimentary rocks of Mid-Norway, and are named, from south to north, MN7 (Gåseland), MN4i (Milne Land–Renland), MN2ii (Hinks Land–Suess Land), MN2iii (Payer Land–Dronning Louise Land), and MN6 (Germania Land). These provide a framework for interpreting the provenance of Greenland–Norway rift sedimentary deposits. The provenance characteristics of Liverpool Land have also been defined, but whether this relatively small region merits a separate provenance status is unclear. Provenance links can be made by comparing the source region sand types with the composition of onshore and offshore sediments from previous studies. Triassic sandstones of the Nordland Ridge and the far south of the Møre Basin, along with Jurassic sandstones of the Heidrun Field in the Haltenbanken area, were derived from the MN4i source region. The provenance of Cretaceous sandstones in East Greenland can be linked to the MN2ii source region. The source of Turonian sandstones on Traill Ø can be pinpointed by zircon U–Pb ages to the Neoproterozoic Lyell Land Group of the Franz Josef Allochthon. Cretaceous sandstones in the Vøring and Møre basins were derived from the MN2iii and MN4i source regions. In addition, some of the Cenomanian–Campanian sedimentary rocks of East Greenland and Mid-Norway contain Permian–Cretaceous-aged zircon grains that are absent from the moraine/outwash samples. The most likely source of these zircon grains is the circum-Arctic region, implying the existence of a long-lived axial drainage system that entered the Greenland–Norway rift from the north.

Background Many behavioural, pharmacological, and metabolic studies in mice require fasting, yet the possibility of fasting-induced torpor affecting the data is rarely considered. Torpor is a state characterised by depressed metabolism and profound alterations to physiology and behaviour. In this study we aimed to determine how the effects of torpor on experimental outcomes could be mitigated. Methods To this end, timing and characteristics of fasting-induced torpor in response to feeding in the morning versus feeding in the night were compared using non-invasive monitoring of peripheral body temperature. Results Night-fed mice entered significantly more torpor bouts per day compared to morning-fed mice (Morning: 2.79±0.197 (mean ± SEM); Night: 4.79±0.533 (mean ± SEM); p=0.0125), but these bouts were shorter on average by ~1.5h. Latency to the first torpor bout following feeding tended to be shorter during night feeding (Morning: 9.57±0.8h (mean ± SEM); Night: 6.66±1.2h (mean ± SEM); p=0.0928). Moreover, torpor bouts typically occurred during the dark phase in the morning-fed group, whilst night feeding resulted in a shift of torpor occurrence to earlier in the day (Morning: 14.2±0.4 ZT h (mean ± SEM); Night: 12.2±0.9 ZT h (mean ± SEM); p=0.0933). There was a high degree of variation in torpor occurrence within and between animals in each group. Conclusions We recommend that feeding time is kept consistent between days and the same across animals to minimise variation in torpor occurrence. Moreover, the timing of food provision may be optimised to allow measurements to be taken during euthermia, to mitigate the effects of torpor on the variables investigated. Finally, we recommend that body temperature is monitored non-invasively to determine when torpor is occurring, and that testing, or sample collection is conducted when the torpor history is comparable between animals.

Background Many behavioural, pharmacological, and metabolic studies in mice require fasting, yet the possibility of fasting-induced torpor affecting data is rarely considered. Torpor is a state characterised by depressed metabolism and profound alterations in physiology and behaviour. In this study, we aimed to determine whether a chronic food restriction paradigm, common in behavioural studies, was sufficient to induce torpor in mice. Methods Mice were food restricted to ~85-90% of their bodyweight, as is typically done, and monitored using continuous thermal imaging. Results We observed that body temperature significantly decreased over days of food restriction, and it was significantly related to the drop in bodyweight (r 2=0.8989, p2=0.8715, p Conclusions Overall, we found that torpor is readily induced in response to food restriction. Considering that hunger is frequently used as a motivational drive in behavioural tasks, it is likely that torpor occurrence is common in such studies, while remaining undetected and unaccounted for. Due to the profound effect of torpor on physiology, it is possible that torpor induction may be confounding subsequent data and represents an important source of variation. We recommend that body temperature is always monitored noninvasively in studies where food restriction is employed, to determine when torpor is occurring, and that torpor history is appropriately controlled for within and across experimental groups.

Students in higher education (HE) are required to complete a variety of writing tasks for coursework and examinations. However, for some students writing presents a major challenge. In the UK, the availability of tools for specialist assessors to help identify difficulties with the quality of written composition is limited. The aim of this study was to develop a practical new tool, the Writing Quality Scale (WQS) for assessing writing quality in HE, that was both easy to use and did not require specialist or subject knowledge. The reliability and validity of the tool and its ability to identify students in HE who may need support were evaluated by examining scripts from 120 students (60 male) aged 17 to 25 years. The WQS was found to have good inter-rater reliability and was sensitive enough to pick up age differences and differentiate between groups of students with and without dyslexia. The WQS will be a useful tool for specialist assessors in HE to help in the identification of those with poor writing quality and to understand more about the nature of their difficulties.